In this exercise we will be using daata that can be obtained from the cityofchicago.org. The link to downloading the data can be found below. - "https://data.cityofchicago.org/api/views/vwwp-7yr9/rows.csv?accessType=DOWNLOAD&bom=true&format=true"

We are interested in viewing the trended volume of crime reports based on where the crime was reported. The areas we selected are as follows. - Street - Residence - Retail Store - Public School/Building

crimeDf$Date <- as.Date(crimeDf$Date, '%m/%d/%Y %H:%M:%S')
crimeDf$Month <- cut(crimeDf$Date, breaks="month")
## Summarize reported 911 calls by Location.Description and Date
# Select only locations of interest/volume
locationVals <- 
  setDT(crimeDf)[,
                 list(
                   num_reports = length(Case.Number != '')
                   ),
                 by = Location.Description]

locationVals <- 
  locationVals[order(locationVals$num_reports, decreasing=TRUE),]

locationVals <- c('STREET','RESIDENCE','SMALL RETAIL STORE',
                  'SCHOOL, PUBLIC, BUILDING')

locationSub <- 
  crimeDf[Location.Description %in% locationVals,]

locationSumm <- 
  setDT(locationSub)[,
                     list(
                       report_count = length(Case.Number != '')
                       ),
                     by=c("Month","Location.Description")]

locationSumm <- locationSumm[(order(locationSumm$Month)),]
monthFactors <- 
  c("2015-01-01","2015-02-01","2015-03-01","2015-04-01",
    "2015-05-01","2015-06-01","2015-07-01","2015-08-01",
    "2015-09-01","2015-10-01","2015-11-01","2015-12-01")

locationSumm$Month <- 
  factor(locationSumm$Month, levels=monthFactors)

f1 <- list(
  family="Arial, sans-serif",
  size=18,
  color="black")

fx1 <- list(
  family="Arial, sans-serif",
  titlefont = f1,
  rangemode="tozero",
  title = "Month"
)

fy1 <- list(
  family="Arial, sans-serif",
  titlefont = f1,
  rangemode="tozero",
  title = "Volume"
)

p <- plot_ly(locationSumm, x=~Month, y=~report_count,
        type="scatter",
        mode="lines",
        color=~Location.Description,
        showlegend=TRUE,
        line = list(
          width=4
        )) %>%
  layout(legend=list(x=1, y=1, size=20),
         xaxis=fx1,
         yaxis=fy1)

Highlighted observations from previous graph

• Street & Residence crime reduces during the holiday season
• Crime in Public Schools reduce drastically during the summer session when kids are outof school
• Crime in small stores are lowest during prime tax refund time (Feb - April)